class_docstr: A bridge that creates an initial decoder state based on the output
  of the encoder. This state is created by passing the encoder outputs
  through an additional layer to match them to the decoder state size.
  The input function remains unmodified.
  
  Args:
    encoder_outputs: A namedtuple that corresponds to the the encoder outputs.
    decoder_state_size: An integer or tuple of integers defining the
      state size of the decoder.
    bridge_input: Which attribute of the `encoder_outputs` to use for the
      initial state calculation. For example, "final_state" means that
      `encoder_outputs.final_state` will be used.
    activation_fn: An optional activation function for the extra
      layer inserted between encoder and decoder. A string for a function
      name contained in `tf.nn`, e.g. "tanh".
code: def _create(self):
      # Concat bridge inputs on the depth dimensions
      bridge_input = nest.map_structure(
          lambda x: tf.reshape(
              x, [self.batch_size, _total_tensor_depth(x)]
          ),
          self._bridge_input,
      )
      bridge_input_flat = nest.flatten([bridge_input])
      bridge_input_concat = tf.concat(bridge_input_flat, 1)
  
      state_size_splits = nest.flatten(self.decoder_state_size)
      total_decoder_state_size = sum(state_size_splits)
  
      # Pass bridge inputs through a fully connected layer layer
      initial_state_flat = tf.contrib.layers.fully_connected(
          inputs=bridge_input_concat,
          num_outputs=total_decoder_state_size,
          activation_fn=self._activation_fn,
      )
  
      # Shape back into required state size
      initial_state = tf.split(
          initial_state_flat, state_size_splits, axis=1
      )
      return nest.pack_sequence_as(
          self.decoder_state_size, initial_state
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import abc
  from pydoc import locate
  import six
  import numpy
  import tensorflow
  from tensorflow.python.util import nest
  from seq2seq.configurable import Configurable
label_desc: Use image node_id 3 for calling the InitialStateBridge obj's underlying member method code with example usage: obj._create() and returns: nest